APPLICATION OF DATA ENVELOPMENT ANALYSIS AND MALMQUIST INDEX ON THE MEASUREMENT OF EFFICIENCY AND PRODUCTIVITY: A CASE STUDY OF RUBBER PRODUCTION IN SOUTHERN THAILAND
DOI:
https://doi.org/10.20319/pijss.2017.32.775786Keywords:
Data Envelopment Analysis, Malmquist Productivity Index, Rubber Production, Southern Thailand, Technical EfficiencyAbstract
The purpose of this study is to investigate the relative technical efficiency of rubber production in Southern of Thailand using the Data Envelopment Analysis (DEA) during the period 2007–2016. Moreover, Malmquist productivity index (MPI) was used to investigate the changes of rubber production efficiency and estimates of the rubber productivity trend. The findings indicated that Trang city has most effective and suitable for the production of rubber when compared to other cities in Southern Thailand. On the other hand, the results also showed that Phuket city has worst scores of efficiency and declination of rubber production. Moreover, MPI model showed the upward productivity trend of rubber production during the time period of the study. The findings from this study can provide important information to farmers, rubber research institutes and Thai government for determining effective strategies to improve productivity and technical efficiency of rubber production. Thai government and rubber research institutes should provide the knowledge, management skills and correct production skills for rubber farmers. Furthermore, rubber research institutes should be at the forefront to increase the rubber yields and provide funding to farmers for increase sustainable rubber production.
References
Barros, C. P., & Leach, S. (2006). Performance Evaluation of the English Premier Football League with Data Envelopment Analysis. Applied Economics, 38(12), 1449-1458. https://doi.org/10.1080/00036840500396574
Baykal, B. (2015). A New Approach To Strategic Planning in Entrepreneurial Process: Effectuation. PEOPLE: International Journal of Social Sciences, 1(2). http://dx.doi.org/10.20319/pijss.2015.12.0118
Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers. The Economic Journal, 73-86. https://doi.org/10.2307/2232257
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
Chauhan, N. S., Mohapatra, P. K., & Pandey, K. P. (2006). Improving Energy Productivity in Paddy Production through Benchmarking-An Application of Data Envelopment Analysis. Energy Conversion and Management, 47(9), 1063-1085. https://doi.org/10.1016/j.enconman.2005.07.004
De Koeijer, T., Wossink, G., Struik, P., & Renkema, J. (2002). Measuring Agricultural Sustainability in Terms of Efficiency: The Case of Dutch Sugar Beet Growers. Journal of Environmental Management, 66(1), 9-17. https://doi.org/10.1006/jema.2002.0578
Fare, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries. American Economic Review, 84(1), 66-83. https://doi.org/10.1016/j.eswa.2015.11.022
Fuentes, R., Fuster, B., & Lillo-Bañuls, A. (2016). A Three-Stage DEA Model to Evaluate Learning-Teaching Technical Efficiency: Key Performance Indicators and Contextual Variables. Expert Systems with Applications, 48, 89-99. https://doi.org/10.1016/j.eswa.2014.11.004
Huguenin, J.-M. (2015). Data Envelopment Analysis and Non-Discretionary Inputs: How to Select the Most Suitable Model Using Multi-Criteria Decision Analysis. Expert Systems with Applications, 42(5), 2570-2581. https://doi.org/10.1016/j.eswa.2014.11.004
Jung, D. B. (2015). Effectiveness of Higher Education to Labor Productivity. PEOPLE: International Journal of Social Sciences, 1(1). http://dx.doi.org/10.20319/pijss.2015.11.1122
KOČIŠOVÁ, K. (2015). Application of the DEA on the Measurement of Efficiency in the EU Countries. Agric. Econ.–Czech, 61, 51-62. https://doi.org/10.17221/107/2014-AGRICECON
Kumarasinghe, H., & Patalee, J. C. E. M. B. (2012). Role of Human Capital in Efficiency Increases: Evidence from a Data Envelopment Analysis of Rubber Smallholdings in Gampaha District. Journal of the Rubber Research Institute of Sri Lanka, 92, 12-21.
Lee, B. L., & Worthington, A. C. (2016). A Network DEA Quantity and Quality-Orientated Production Model: An Application to Australian University Research Services. Omega, 60, 26-33. https://doi.org/10.1016/j.omega.2015.05.014
Liu, J. S., Lu, L. Y., Lu, W.-M., & Lin, B. J. (2013). Data Envelopment Analysis 1978–2010: A Citation-Based Literature Survey. Omega, 41(1), 3-15. https://doi.org/10.1016/j.omega.2010.12.006
Liu, Y., Mu, C., Jiang, K., Zhao, J., Li, Y., Zhang, L., . . . Ma, T. (2015). A Tetraphenylethylene Core-Based 3D Structure Small Molecular Acceptor Enabling Efficient Non-Fullerene Organic Solar Cells. Advanced Materials, 27(6), 1015-1020. https://doi.org/10.1002/adma.201404152 https://doi.org/10.1002/adma.201570038
Longpichai, O., Perret, S. R., & Shivakoti, G. P. (2012). Role of Livelihood Capital in Shaping the Farming Strategies and Outcomes of Smallholder Rubber Producers in Southern Thailand. Outlook on Agriculture, 41(2), 117-124. https://doi.org/10.5367/oa.2012.0085
Mustapha, N. H. N. (2011). Technical Efficiency for Rubber Smallholders under RISDA’s Supervisory System Using Stochastic Frontier Analysis. Journal of Sustainability Science and Management, 6(1), 156-168.
Nomikos, N. K., & Pouliasis, P. K. (2011). Forecasting Petroleum Futures Markets Volatility: the Role of Regimes and Market Conditions. Energy Economics, 33(2), 321-337. https://doi.org/10.1016/j.eneco.2010.11.013
Picazo-Tadeo, A. J., Gómez-Limón, J. A., & Reig-Martínez, E. (2011). Assessing Farming Eco-Efficiency: A Data Envelopment Analysis Approach. Journal of Environmental Management, 92(4), 1154-1164. https://doi.org/10.1016/j.jenvman.2010.11.025
Rubber Research Institute of Thailand (RRIT), 2016 Thai Rubber Statistics. Ministry of Agriculture and Cooperative, Bangkok, Thailand. Available at http://www.thainr.com/en/index.php?detail=stat-thai (accessed October 2016).
Sahin, G., Gokdemir, L., & Ozturk, D. (2016). Global Crisis and its Effect on Turkish Banking Sector: A Study with Data Envelopment Analysis. Procedia Economics and Finance, 38, 38-48. https://doi.org/10.1016/S2212-5671(16)30174-5
Shrestha, R. B., Huang, W.-C., Gautam, S., & Johnson, T. G. (2016). Efficiency of Small Scale Vegetable Farms: Policy Implications for the Rural Poverty Reduction in Nepal. Agricultural Economics (Zemedelská Ekonomika), 62(4), 181-195. https://doi.org/10.17221/81/2015-AGRICECON
Singh, G., Singh, S., & Singh, J. (2004). Optimization of Energy Inputs for Wheat Crop in Punjab. Energy Conversion and Management, 45(3), 453-465. https://doi.org/10.1016/S0196-8904(03)00155-9
Tsolas, I. E., & Charles, V. (2015). Incorporating Risk into Bank Efficiency: A Satisficing DEA Approach to Assess the Greek Banking Crisis. Expert Systems with Applications, 42(7), 3491-3500. https://doi.org/10.1016/j.eswa.2014.12.033
Xue, X., Shen, Q., Wang, Y., & Lu, J. (2008). Measuring the Productivity of the Construction Industry in China by Using DEA-Based Malmquist Productivity Indices. Journal of Construction Engineering and Management, 134(1), 64-71. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:1(64)
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